Olympics

Olympic Rings

Olympic Rings

Intro

The Olympics are a worldwide celebration of the best athletes in the world that promotes peace and unity. There are no honors greater for athletes than winning a gold medal for their country. This incredible achievement may be influenced by obvious variables such as physical traits of the athletes, the type of olympics (summer or winter), or variables that one would not think are immediately related to sports. We suspect that factors such as a country’s total GDP and Population. We explore if these factors influence the number of medals won in the Olympics in this blog. Our aim is to deepen our understanding of what factors influence a country’s success in the games and spread the information in hopes that there may be a solution to even the playing field.

USA Medal Exploration

The above medal time graph demonstrates the number of medals that the United States won each year that the Olympics were held. This allows us to see how the United States has performed at the Olympic stage. The graph has very sharp curves up and down which represent the medal differences between the summer and winter olympics. The USA tends to win more medals in the summer Olympics than the Winter olympics.

2016 Olympic Data Analysis

The above graph shows the relationship between a Country’s GDP and the number of medals that they won at the 2016 Olympic games. There is a large cluster of countrys with low GDP and low medal count, as there are a lot of small countries that are not large medal winners. This graph shows that only two countries, namely the United States and China, are above the 50 medal count threshold. Consequently, those two countries have much greater GDP in comparison to other countries. The size of the points is related to that countries relative population. We can see that population is not as predictive of medal count as GDP is. This is because there are large and small points at both directions of the y axis (medal count).

GDP and Population Country Maps (2010)

This map displays Total GDP in 2010 for countries around the world. Lighter shades indicate a lower total GDP, while darker shades represent a higher GDP. Countries such as China, The United States of America, and Japan are among the countries with the highest Total GDP. Users can hover over the country of their choice to identify the country’s name and its Total GDP.

This map displays populations for countries around the world in 2010. Lighter shades indicate a relatively low population, while dark shades indicate a relatively high population. China and India are among the countries with the highest total population by a considerable margin. Users can hover over the country of their choice to identify the country’s name and its population.

Population and Medals won in 2016 Olympics

This map displays the medals won in the 2016 Olympics versus the population of countries around the world in 2016. Lighter shades indicate a relatively low number of medals when compared to the population, while dark shades indicate a high number of medals when compared to the population. Grey represents the countries who did not win medals during the 2016 Olympics. Georgia, Azerbaijan, and Denmark are among the countries with the highest number of medals in context of their populations. Countries with high GDPs or populations such as the United States, China, Japan, and Brazil all won medals during the Olympics. Users can hover over the countries to view the country’s name and Medals won in comparison to their population. The maps were created using ggplot in R.

Athlete Medal Analysis

Height

##   cluster min  Q1 median  Q3 max     mean       sd     n missing
## 1       1 136 163    167 170 179 166.0061 6.077095  9903       0
## 2       2 164 187    190 195 223 191.3349 6.662754  6679       0
## 3       3 162 176    180 183 203 179.3911 4.734164 13599       0

Weight

##   cluster min Q1 median Q3 max     mean        sd     n missing
## 1       1  28 55     59 64  90 58.79935  6.840851  9903       0
## 2       2  70 87     92 98 182 94.04844 11.061994  6679       0
## 3       3  54 70     75 79 104 74.67582  6.286214 13599       0

Fritz explain your findings…

Conclusion

Fritz write a conclusion

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